Daniel J. Panyard

This study identifies plasma proteins associated with insulin sensitivity across diverse populations and shows their response to interventions, with some proteins suggesting causal relationships and therapeutic targets.

This study identifies plasma proteomic signatures that modestly improve prediction of incident type 2 diabetes compared to clinical and genetic factors.

This paper develops a plasma proteomic signature for predicting atherosclerotic cardiovascular disease risk using UK Biobank data and finds it modestly improves prediction over clinical and genetic factors.

The paper performs a metabolome-wide association study to identify CSF metabolite-phenotype associations in neurological and psychiatric disorders.